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7b00e11
docs(agent-platform): add Agent Memory research-preview pages
hongyi-chen May 16, 2026
1564a8d
docs(agent-memory): scrub internals, downsize API page, tighten tone
hongyi-chen May 16, 2026
ef5d17f
docs(agent-memory): drop remaining internal-implementation details
hongyi-chen May 16, 2026
9bce66c
docs(agent-memory): use canonical "agent identity" terminology
hongyi-chen May 16, 2026
2ea77ff
docs(agent-memory): consolidate research-preview docs into a single page
hongyi-chen May 18, 2026
5648a5a
docs(agent-memory): audit polish pass on the consolidated research-pr…
hongyi-chen May 18, 2026
527a384
Merge branch 'hyc/orchestration-launch' into hyc/orch/memory
hongyi-chen May 18, 2026
ed1415b
docs(agent-memory): rewrite as unified SEO/waitlist page
hongyi-chen May 18, 2026
c8a6458
docs(agent-memory): polish hero opener for clarity
hongyi-chen May 19, 2026
b740473
docs(agent-memory): consolidate PR #95 content, move to top-level Mem…
hongyi-chen May 19, 2026
f13928c
docs(agent-memory): address Suraj's review feedback
oz-agent May 19, 2026
479b0c6
docs(agent-memory): lead with async + Oz-as-the-layer framing
oz-agent May 19, 2026
6c93d6f
docs(agent-memory): polish pass
oz-agent May 19, 2026
0c488a6
docs(agent-memory): de-marketing pass, dev-doc tone
oz-agent May 19, 2026
10c0d32
Merge branch 'hyc/orchestration-launch' into hyc/orch/memory
hongyi-chen May 19, 2026
a93275e
docs(agent-memory): address all of Suraj's review comments
oz-agent May 19, 2026
ac96a45
docs(agent-memory): polish pass after review-comment rewrite
oz-agent May 19, 2026
1258076
docs(agent-memory): make self-hosted explicit + small polish
oz-agent May 19, 2026
0064236
docs(agent-memory): cross-link self-hosting + Oz API, tighten store b…
oz-agent May 19, 2026
7e50661
docs(agent-memory): final scan nits
oz-agent May 19, 2026
e147217
Merge branch 'hyc/orchestration-launch' into hyc/orch/memory
hongyi-chen May 19, 2026
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75 changes: 75 additions & 0 deletions src/content/docs/agent-platform/agent-memory/index.mdx
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---
title: Agent Memory (Research Preview)
description: >-
Agent Memory is a persistent, cross-harness memory layer for agents in
Warp — Warp Agent, Claude Code, Codex, Gemini, and others — that learns
over time.
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nit: I think the cross-harness part covers it?

sidebar:
label: "Agent Memory (Research Preview)"
---
:::caution
Agent Memory is in **research preview** and is enabled per team for design partners. [Join the waitlist](https://warp.dev/oz/agent-memory#waitlist) to request access for your team.
:::

Agent Memory is a persistent memory layer that lives on Warp and is shared across every supported agent harness — the built-in Warp Agent, Claude Code, Codex, Gemini, and others. Agents read from and write to it as they run, so durable facts, decisions, and outcomes from one conversation are available to the next, regardless of which harness, machine, or teammate triggers it.
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s/Warp/Oz?

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Also Gemini isn't officially supported in Oz yet, right?


Memory creation and retrieval are asynchronous and run in the background, so they don't consume tokens or add latency to the active task.

[Join the Agent Memory waitlist](https://warp.dev/oz/agent-memory#waitlist)

## Key features
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  • Supported for both local interactive and background cloud agents
  • Fully accessible via API
  • Traceability: it is possible to determine which context influenced a given agent run
  • Auditability: changes to memories produce a changelog, so the evolution of any memory can be inspected
  • Self-hostable: enterprises can host their own instance to satisfy security, privacy, and compliance requirements


* **Cross-harness memory** — Memory is shared across every supported harness (Warp Agent, Claude Code, Codex, Gemini, and others). No per-harness setup, and no separate memory service to maintain.
* **Asynchronous by design** — Memory creation runs after a conversation ends. Retrieval runs in the background during a run. Neither consumes tokens or adds latency to the active task.
* **Automatic memory from conversations** — When a conversation ends, Warp extracts durable facts, learnings, and outcomes and writes them as memories. New knowledge merges with existing memories or supersedes them on conflict.
* **Personal and team stores** — Stores are owned by a user or a team. Personal stores are private; team stores are shared across the team and any agents the team authorizes.
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I would focus more on the sharing here, less on personal - highlighting that memory is agent-scoped and can be shared across agents.

* **Per-agent access and instructions** — Attach stores to specific agents with read-only or read-write access. Per-store instructions tell each agent how and when to use the store.
* **Deletion safety** — A store can't be deleted while it's attached to a live agent.
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seems irrelevant?


## Where Agent Memory runs

Agent Memory runs entirely on Warp's infrastructure. Storage, memory creation, and retrieval are all hosted services — there's no separate memory backend for you to operate. Because the layer lives on Warp, the same memory is accessible from any agent you run through Warp:
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This feels pretty strong - we should mention somewhere that it can be self-hosted


* The local Warp Agent.
* Oz cloud agents triggered from the CLI, web app, schedules, or integrations.
* Third-party harnesses on Warp: Claude Code, Codex, Gemini, and others as they're added.
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It's only supported for third party harnesses running in Oz (not 3p harnesses running locally), at least for now


Memory stays bound to its owner (a user or a team), independent of which harness reads or writes.

## Memory stores

A memory store is a named container of memories. By default, each agent has its own store and writes to it as it runs. Stores can also be shared across multiple agents when they need the same knowledge.

* **Personal stores** — Owned by a user. Hold preferences, working notes, and individual patterns.
* **Team stores** — Owned by a team. Hold shared knowledge like deployment runbooks, code review conventions, or on-call procedures. Every team member and any team-authorized agent can read from the same store.

Use multiple stores to keep contexts separate, and share stores across agents when needed. For example, a code review agent can have its own store of review patterns, while a repo-specific store of architectural decisions is shared between the code review agent and a Sentry triage agent so both reason about the same codebase.

## Automatic memory from conversations

When a conversation finishes, Warp extracts durable facts, learnings, and outcomes from what happened and writes them as memories. Memory creation runs in the background after the conversation ends, so it doesn't consume tokens or add latency during the run that produced it.

* **Sparse by design** — Routine work produces nothing. Only meaningful, reusable knowledge becomes a memory.
* **Learns over time** — New knowledge merges into existing memories or supersedes them on conflict.
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I would remove this and instead mention that memories evolve over time and can be updated by agents to resolve contradicitons, etc.


You can also explicitly tell Warp to remember something during a conversation, and it lands in the appropriate store.

## How agents use memory

When an agent starts a task, Warp searches the stores the agent can access for relevant memories and injects them as context. The search runs in the background, so the agent only sees the memories returned. Agents can also retrieve additional memories on demand mid-conversation when they determine it's relevant, similar to how they consult rules or Codebase Context. You don't need to write retrieval queries or pre-load memory.

## Attaching memory to your agents

Attach stores to agents with read-only or read-write access. Each attachment includes a free-form instruction string that tells the agent how and when to use the store — for example, "Reference this store for team naming conventions" or "Write a new memory after each successful deployment." Without instructions, the agent has access to the store but no guidance on when to read or write.

## Join the waitlist

Agent Memory is rolling out to design partner teams during research preview. [Join the waitlist](https://warp.dev/oz/agent-memory#waitlist) to request access.

## Related pages

* [Codebase Context](/agent-platform/capabilities/codebase-context/) — Let agents understand your codebase through semantic indexing.
* [Rules](/agent-platform/capabilities/rules/) — Define global and project-level guidelines that shape agent behavior.
* [Skills](/agent-platform/capabilities/skills/) — Reusable, scoped instructions that teach agents how to perform specific tasks.
* [Agent profiles and permissions](/agent-platform/capabilities/agent-profiles-permissions/) — Control what permissions and autonomy agents have.
* [Cloud agents overview](/agent-platform/cloud-agents/overview/) — Run background agents with team-wide observability.
4 changes: 4 additions & 0 deletions src/content/docs/agent-platform/capabilities/skills.mdx
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Expand Up @@ -411,6 +411,10 @@ Warp maintains a public collection of ready-to-use skills in the [warpdotdev/oz-

These same skills also appear as suggested agents in the [Oz web app](/agent-platform/cloud-agents/oz-web-app/), where you can run them directly in the cloud.

## Suggested Skills from Agent Memory

Promoting recurring patterns from [Agent Memory](/agent-platform/agent-memory/) into reviewable skill drafts is in design as part of the research preview. See the Agent Memory page for current status.

## Invoking skills with a prompt

You can pass additional context or instructions to a skill when invoking it with a slash command.
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6 changes: 6 additions & 0 deletions src/sidebar.ts
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Expand Up @@ -246,6 +246,12 @@ export const sidebarTopics: StarlightSidebarTopicsUserConfig = [
'agent-platform/getting-started/faqs',
],
},
{
label: 'Memory (Research Preview)',
items: [
{ slug: 'agent-platform/agent-memory', label: 'Agent Memory' },
],
},
{
label: 'Warp Agents',
items: [
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5 changes: 5 additions & 0 deletions vercel.json
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Expand Up @@ -9572,6 +9572,11 @@
"source": "/oz",
"destination": "/agent-platform/cloud-agents/overview/",
"statusCode": 308
},
{
"source": "/agent-platform/capabilities/agent-memory",
"destination": "/agent-platform/agent-memory/",
"statusCode": 308
}
]
}
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